In future work, it would be interesting to explore different approaches to learning deep models in the PCL problem.
One direction would be to adapt the method of moment matching, which has been studied extensively in the instrumental variable literature [1]}. Moreover, [2]} recently developed a novel adversarial method to solve a class of functional equations, which would be also a promising approach in the PCL problem. In the RL context, [3]} shows an the interesting connection between PCL learning and off-policy evaluation in a partially observable Markov decision process, and we believe that adapting DFPV to this setting will be of great value.
